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Score optimization and template updating in a biometric technique for authentication in mobiles based on gestures

机译:基于手势的生物识别技术中的分数优化和模板更新,用于手机认证

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摘要

This article focuses on the evaluation of a biometric technique based on the performance of an identifying gesture by holding a telephone with an embedded accelerometer in his/her hand. The acceleration signals obtained when users perform gestures are analyzed following a mathematical method based on global sequence alignment. In this article, eight different scores are proposed and evaluated in order to quantify the differences between gestures, obtaining an optimal EER result of 3.42% when analyzing a random set of 40 users of a database made up of 80 users with real attempts of falsification. Moreover, a temporal study of the technique is presented leeding to the need to update the template to adapt the manner in which users modify how they perform their identifying gesture over time. Six updating schemes have been assessed within a database of 22 users repeating their identifying gesture in 20 sessions over 4 months, concluding that the more often the template is updated the better and more stable performance the technique presents.
机译:本文着重于通过将具有嵌入式加速度计的电话握在手中来对基于识别手势性能的生物识别技术进行评估。根据基于全局序列比对的数学方法,分析用户执行手势时获得的加速度信号。在本文中,提出并评估了八个不同的分数,以量化手势之间的差异,在分析由80个用户组成的数据库中的40个用户的随机集,并进行真实的伪造尝试时,获得的最佳EER结果为3.42%。此外,提出了对该技术的时间研究,其目的在于更新模板以适应用户随着时间修改他们如何执行其识别手势的方式。在22个用户的数据库中,已经评估了六个更新方案,该数据库在4个月内的20个会话中重复了其识别手势,结论是模板更新的频率越高,该技术所呈现的性能越好且越稳定。

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